# corMartins

From ape v2.1-1
by Emmanuel Paradis

##### Martins's (1997) Correlation Structure

Martins and Hansen's (1997) covariance structure: $$V_{ij} = \gamma \times e^{-\alpha t_{ij}}$$ where $t_{ij}$ is the phylogenetic distance between taxa $i$ and $j$ and $\gamma$ is a constant.

- Keywords
- models

##### Usage

```
corMartins(value, phy, form=~1, fixed = FALSE)
## S3 method for class 'corMartins':
coef(object, unconstrained = TRUE, ...)
## S3 method for class 'corMartins':
corMatrix(object,
covariate = getCovariate(object), corr = TRUE, ...)
```

##### Arguments

- value
- The $\alpha$ parameter
- phy
- An object of class
`phylo`

representing the phylogeny (with branch lengths) to consider - object
- An (initialized) object of class
`corMartins`

- corr
- a logical value. If 'TRUE' the function returns the correlation matrix, otherwise it returns the variance/covariance matrix.
- fixed
- an optional logical value indicating whether the coefficients should be allowed to vary in the optimization, ok kept fixed at their initial value. Defaults to 'FALSE', in which case the coefficients are allowed to vary.
- form
- ignored for now.
- covariate
- ignored for now.
- unconstrained
- a logical value. If 'TRUE' the coefficients are returned in unconstrained form (the same used in the optimization algorithm). If 'FALSE' the coefficients are returned in "natural", possibly constrained, form. Defaults to 'TRUE'
- ...
- some methods for these generics require additional arguments. None are used in these methods.

##### Value

- An object of class
`corMartins`

or the alpha coefficient from an object of this class or the correlation matrix of an initialized object of this class.

##### References

Martins, E. P. and Hansen, T. F. (1997) Phylogenies and the comparative
method: a general approach to incorporating phylogenetic information
into the analysis of interspecific data. *American Naturalist*,
**149**, 646--667.

##### See Also

*Documentation reproduced from package ape, version 2.1-1, License: GPL (>= 2)*

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